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This is the 5th edition with a publication date of 3/22/2010.

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Summary

An update to a classic in the field of surveying, this is one of the few books that deals with the important issue of error in spatial data. Originally written for surveyors, it has expanded over the years to encompass the needs of new spatial technologies as they've been introduced (GPS, GIS) and new analytical techniques as they find acceptance. This Fifth Edition offers new screenshots to guide students through the exercises, more problems, more worked solutions in the solutions manual, as well as PowerPoint slides from the author's lectures.

Author Biography

Charles D. Ghilani, PhD, is Professor of Engineering in the Surveying Engineering program at The Pennsylvania State University.

Table of Contents

PREFACE.

ACKNOWLEDGMENTS.

1 Introduction.

1.1. Introduction.

1.2. Direct and Indirect Measurements.

1.3. Measurement Error Sources.

1.4. Definitions.

1.5. Precision versus Accuracy.

1.6. Redundant Observations in Surveying and Their Adjustment.

1.7. Advantages of Least Squares Adjustment.

1.8. Overview of the Book.

Problems.

2 Observations and Their Analysis.

2.1. Introduction.

2.2. Sample versus Population.

2.3. Range and Median.

2.4. Graphical Representation of Data.

2.5. Numerical Methods of Describing Data.

2.6. Measures of Central Tendency.

2.7. Additional Definitions.

2.8. Alternative Formula for Determining Variance.

2.9. Numerical Examples.

2.10. Derivation of the Sample Variance (Bessel’s Correction).

2.11. Software.

Problems.

Practical Exercises.

3 Random Error Theory.

3.1. Introduction.

3.2. Theory of Probability.

3.3. Properties of the Normal Distribution Curve.

3.4. Standard Normal Distribution Function.

3.5. Probability of the Standard Error.

3.6. Uses for Percent Errors.

3.7. Practical Examples.

Problems.

Programming Problems.

4 Confidence Intervals.

4.1. Introduction.

4.2. Distributions Used in Sampling Theory.

4.3. Confidence Interval for the Mean: t statistic.

4.4. Testing the Validity of the Confidence Interval.

4.5. Selecting a Sample Size.

4.6. Confidence Interval for a Population Variance.

4.7. Confidence Interval for the Ratio of Two Population Variances.

4.8. Software.

Problems.

5 Statistical Testing.

5.1. Hypothesis Testing.

5.2. Systematic Development of a Test.

5.3. Test of Hypothesis for the Population Mean.

5.4. Test of Hypothesis for the Population Variance.

5.5. Test of Hypothesis for the Ratio of Two Population Variances.

5.6. Software.

Problems.

6 Propagation of Random Errors in Indirectly Measured Quantities.

6.1. Basic Error Propagation Equation.

6.2. Frequently Encountered Specific Functions.

6.3. Numerical Examples.

6.4. Software.

6.5. Conclusions.

Problems.

Practical Exercises.

7 Error Propagation in Angle and Distance Observations.

7.1. Introduction.

7.2. Error Sources in Horizontal Angles.

7.3. Reading Errors.

7.4. Pointing Errors.

7.5. Estimated Pointing and Reading Errors with Total Stations.

7.6. Target-Centering Errors.

7.7. Instrument-Centering Errors.

7.8. Effects of Leveling Errors in Angle Observations.

7.9. Numerical Example of Combined Error Propagation in a Single Horizontal Angle.

7.10. Using Estimated Errors to Check Angular Misclosure in a Traverse.

7.11. Errors in Astronomical Observations for Azimuth.

7.12. Errors in Electronic Distance Observations.

7.13. Software.

Problems.

Programming Problems.

8 Error Propagation in Traverse Surveys.

8.1. Introduction.

8.2. Derivation of Estimated Error in Latitude and Departure.

8.3. Derivation of Estimated Standard Errors in Course Azimuths.

8.4. Computing and Analyzing Polygon Traverse Misclosure Errors.

8.5. Computing and Analyzing Link Traverse Misclosure Errors.

8.6. Software.

8.7. Conclusions.

Problems.

Programming Problems.

9 Error Propagation in Elevation Determination.

9.1. Introduction.

9.2. Systematic Errors in Differential Leveling.

9.3. Random Errors in Differential Leveling.

9.4. Error Propagation in Trigonometric Leveling.

Problems.

Programming Problems.

10 Weights of Observations.

10.1. Introduction.

10.2. Weighted Mean.

10.3. Relation between Weights and Standard Errors.

10.4. Statistics of Weighted Observations.

10.5. Weights in Angle Observations.

10.6. Weights in Differential Leveling.

10.7. Practical Examples.

Problems.

11 Principles of Least Squares.

11.1. Introduction.

11.2. Fundamental Principle of Least Squares.

11.3. Fundamental Principle of Weighted Least Squares.

11.4. Stochastic Model.

11.5. Functional Model.

11.6. Observation Equations.

11.7. Systematic Formulation of the Normal Equations.

11.8. Tabular Formation of the Normal Equations.

11.9. Using Matrices to Form Normal Equations.

11.10. Least Squares Solution of Nonlinear Systems.

11.11. Least Squares Fit of Points to a Line or Curve.

11.12. Calibration of an EDM Instrument.

11.13. Least Squares Adjustment Using Conditional Equations.

11.14. The Previous Example Using Observation Equations.

11.15. Software.

Problems.

12 Adjustment of Level Nets.

12.1. Introduction.

12.2. Observation Equation.

12.3. Unweighted Example.

12.4. Weighted Example.

12.5. Reference Standard Deviation.

12.6. Another Weighted Adjustment.

12.7. Software.

Problems.

Programming Problems.

13 Precisions of Indirectly Determined Quantities.

13.1. Introduction.

13.2. Development of the Covariance Matrix.

13.3. Numerical Examples.

13.4. Standard Deviations of Computed Quantities.

Problems.

Programming Problems.

14 Adjustment of Horizontal Surveys: Trilateration.

14.1. Introduction.

14.2. Distance Observation Equation.

14.3. Trilateration Adjustment Example.

14.4. Formulation of a Generalized Coefficient Matrix for a More Complex Network.